Delay Prediction in the Operation of Flights

This project utilizes machine learning techniques to predict flight delays and analyze contributing factors. Implemented in Python, it offers insights into historical flight data using libraries.

Repo: github.com

  • Tech Stack: Python, pandas, scikit-learn, matplotlib, seaborn.

Key Features

  • Built a ML model to predict flight delays and analyzing the factors contributing to flight delays by leveraging historical flight data and employing machine learning algorithms.
  • Achieved a testing score of 0.8467 and an accuracy of approximately 84.67% on the test set using the Bernoulli Naive Bayes Classifier model.
  • Visualization of flight delay patterns and insights.